Monitors and troubleshoots GKE TPU workloads, nodes, and node pools using GKE system metrics and PromQL. Use when monitoring TensorCore duty cycle, TPU memory, node readiness, multi-host TPU node pool availability, host maintenance or preemption interruptions, and calculating MTTR or MTBI metrics for GKE TPUs. Don't use for general non-TPU GKE workload monitoring or non-metric TPU debugging.
Install
npx skills add google/skills --skill gke-ai-troubleshooting-tpu-metrics-monitoringnpx skills add google/skills --skill gke-ai-troubleshooting-tpu-metrics-monitoring -a claude-code -gnpx skills add google/skills --skill gke-ai-troubleshooting-tpu-metrics-monitoring -a codex -ggemini skills install https://github.com/google/skills.git --path skills/cloud/gke-ai-troubleshooting-tpu-metrics-monitoringgh skill install google/skills gke-ai-troubleshooting-tpu-metrics-monitoringgit clone --depth 1 https://github.com/google/skills /tmp/google__skills
mkdir -p ~/.claude/skills ~/.agents/skills
cp -R /tmp/google__skills/skills/cloud/gke-ai-troubleshooting-tpu-metrics-monitoring ~/.claude/skills/gke-ai-troubleshooting-tpu-metrics-monitoring # Claude Code
cp -R /tmp/google__skills/skills/cloud/gke-ai-troubleshooting-tpu-metrics-monitoring ~/.agents/skills/gke-ai-troubleshooting-tpu-metrics-monitoring # Codex, Cursor, Gemini CLI, Copilot, OpenCode